1. Field of the Invention
This invention relates in general to a storage system accounting, and more particularly to a method, apparatus and program storage device for providing real-time file system charge-back accounting with real time historical minimum and maximum usage per user or group during a report cycle.
2. Description of Related Art
In today's information age, computer and communication systems often require large amounts of data storage. More and more frequently, access to data storage is being provided over communication networks. Among other things, this makes data storage resources available to a number of data storage users.
Storage infrastructures of enterprises are feeling a strain as the huge demand for storage continues to rapidly increase. Escalating capacity and bandwidth requirements cause costs to soar as resource-constrained organizations struggle to manage the complexity and sheer volume of data that must be stored, accessed, and protected.
The increase in average file size (text-based to multimedia) continues to grow. New applications are driving storage capacity upward and introducing new types of data. At the same time, Internet access devices, such as mobile phones and Personal Digital Assistants (PDAs), are getting smaller with less processing power, less storage, and smaller screen sizes. This trend implies that more content will have to be processed and stored rather than within the access device itself.
Most businesses today are faced with high growth in the amount of data they have to store, but IT budgets are flat, or being reduced. IT can no longer afford to keep all their data on high-end storage platforms or staffing levels to manage large numbers of storage targets. The answer is to produce a small set of storage tiers that align with business requirements to provide the optimum service level at the lowest cost. Tiered Storage School will help in understanding which technologies are available for implementing a tiered storage strategy.
Information Lifecycle Management (ILM) is a process that includes Information Technology (IT) staff making decisions about what data should reside where in the physical infrastructure. ILM is a process in which people, processes, and technologies deal with data from cradle to grave. Data has different value at inception than it does at death, so it shouldn't be treated the same way during each phase of its lifetime.
However, a distinction may be made between Data Lifecycle Management (DLM) and ILM. DLM is the infrastructural element and ILM is the macro-level element that assigns both subjective and objective value. ILM relates not only to an application, but also to where the information itself resides in the company as a whole. DLM, which involves the infrastructural component of what goes where and when, is very similar to the traditional Hierarchical Storage Management (HSM) that has existed in the mainframe world since inception. The primary difference is that HSM is a single-server, single storage stack methodology for moving data down the physical stack in order to lower the cost of primary storage, whereas DLM architectures automate the processes involved, typically organizing data into separate tiers according to specified policies, and automating data migration from one tier to another based on those criteria. DLM includes two tiers. There is the physical tier of actual storage where data resides, including disk arrays of all sizes and tapes, and then there is the process tier for moving data between those elements.
Companies today are constructing tiered storage infrastructures. These companies continue to deploy storage systems that deliver many different classes of storage ranging from high performance/high cost to high capacity/low cost. Through the deployment of SANs, many of these storage assets are now physically connected to servers that run many different types of applications and create many kinds of information. Finally, with the arrival of network-resident storage services for distributed management of volume, files, and data replication managers can intelligently manage storage assets to meet the needs of many different applications across the network instead of device by device.
Accordingly, the growing importance of data as a corporate asset puts increasing pressure on organizations to protect and manage storage to ensure its continuous availability. As sites are faced with deploying larger and more complex storage infrastructure, storage management costs compound quickly and technology planning becomes riskier. Moreover, the rapid evolution of technology mandates training of specialized personnel to maximize performance gains and ensure compatibility with emerging standards.
Because of these factors, it is important that today's accounting process measure and assign resource and service utilization accurately. An effective way to measure, report, and charge for the operational costs and services is to integrate the accounting process with the measurement system. As a result, the role of accounting has expanded from capacity planning, resource utilization, and performance monitoring to one of measuring and charging operational costs for technical resources and end user services provided by data center. Accounting process must gather accounting information from different sources. The accounting process needs to be closely linked with both the Service Level Agreements (SLA) and the reporting process to successfully manage and charge storage related costs.
With data processing, each department and every project produces costs. The goal of the accounting and chargeback system is to identify total costs for each cost categories, what caused the costs, who caused the costs, how to distribute the cost and who to bill. An essential requirement of the accounting and chargeback system is to accurately identify all costs, measure the usage and correctly distribute the costs. All resources and services must be analyzed to determine who is consuming the resource or service and what costs are associated with the resource or service so the cost can be charged. This process is not simple, and requires detailed knowledge of the systems to recognize the correct data and correctly associate the data in the accounting and chargeback system.
The main purpose of an accounting system is chargeback. Chargeback is when the cost of services provided are identified and charged to the users and recipients of the services. Without charging for the services, the process of accounting for services is of little value. The accounting system is used to discover resource usage and assign the various resource usages to different causes. By assigning a value to each resource usage, a chargeback system is developed.
File system chargeback accounting is point-in-time in nature with today's file systems. Normally the functionality is tied to a file system's user or group quota and some independent reporting utility. The space reported is generated from the current quota accounting within the file system via some customized scripting. The major drawback is space utilization can dynamically change, sometimes significantly, during a reporting cycle. There is no way to determine that a user has potentially large cyclic space usage. Additionally, some quota implementations only report the used disk space and do not consider allocated space.
Another solution that exists in some space reporting tools today is a sampling method which estimates the amount of space used by a user or application. The problem with this approach is the sample period can be very costly and time consuming. Additionally, the results are only an estimation of the space utilization. Additionally, this type of method can only categorize file systems and applications it knows about. New file systems or application support in a customer environment would need to be added. Some SAN providers provide chargeback at a logical LUN granularity, but not at a file system user or group granularity.
It can be seen then that there is a need for a method, apparatus and program storage device for providing file system chargeback accounting with real time historical minimum and maximum usage per management object, e.g., user or group, during a report cycle.